Learn to Think Critically About Data Filtering

A Guide to the Interactive Light Index

The interactive index is more than a convenient list of links - it shows how to search, filter and organise information across a growing landscape of resources. While browsing, you're also practising essential AI literacy skills: critical thinking, structuring, and understanding how data choices shape what you see.

Updated 7 November 2025 7-minute read

TL;DR Summary

The Light Index is a tool that helps users explore resources while learning AI literacy skills like filtering, critical thinking, and understanding data bias. It's easy to use, privacy-friendly, and great for classrooms or teams.

What You See

At the top of the page is a toolbar that lets you adjust the view, search query and filter options. We use this tool in several places on our site to facilitate navigation.

Light Index toolbar with filters and view options — Figure 1. The Light Index toolbar showing view, search, filter, and sort options.

This toolbar includes:

Two view buttons: grid or list
A search bar: with live results and support for advanced search
A category selector: main categories, shown as coloured tags
A sort menu: such as Phase, Newest, Popularity
A Reset button: to restore default settings
An Expand all button: to reveal all additional details at once
A read page indicator: viewed cards appear faded to show they've been readed
Sharable deep links: URL parameters store settings (e.g. ?category=AI&sort=az)

Below that, you'll find a series of cards - each showing a title, category, tags, reading time, publication date and short summary, with additional expandable details. Some lists also include a checkbox that allows you to mark or tick cards. Click any card to open the related page.

💡 Your settings stay on your device. No cookies, no tracking.

Step by step, you'll see how metadata (such as category, tags and date) helps to structure knowledge and connect ideas across policy, practice and professional development.

What You Learn

The index is both a practical tool and a learning exercise in digital criticality. It reveals that every search is a design choice: what appears first, what disappears - and who decides.

Metadata as context: You learn that contextual information is never neutral; it shapes how knowledge is interpreted.
Transparency and control: By filtering and sorting for yourself, you experience what autonomy means in a data environment.
Information architecture: The way categories and tags are built helps you reflect on structure, hierarchy and meaning.

In short: the index doesn't just help you find - it helps you understand how finding works.

The Art of Advanced Search

Most users just type a few words. But those who dig deeper discover that the search bar can do much more. Advanced Search lets you specify exactly what you want - and what to leave out - just like real data or AI systems.

“Advanced Search - the hidden layer of transparency”

How it works:

Space = AND: ai ethics finds cards containing both words.
Quotation marks = exact phrase: "teacher training" finds only exact matches.
Minus sign = exclude: -policy removes all cards related to “policy”.
OR or | = alternatives: rubric OR "grading guide" shows cards that include either phrase.
Field filters:
- title: searches in titles → title:"AI tools"
- tag: searches in tags → tag:assessment
- content: searches in summaries and details → content:governance
Card status:
- read / unread: filters results based on your reading history. Use is:read to show cards you have already viewed, or is:unread to display only new content.
- checked / unchecked: use the checkboxes on cards to mark items you have already reviewed, completed, or wish to keep track of. This option is only available for lists that include checkboxes. Use is:checked to show all marked cards, or is:unchecked for cards that are not yet marked.

Figure 2. Example Light Index card with highlighted areas for advanced search filters (`title:`, `tag:`, `content:`) and read state (`is:read` / `is:unread`). Readed cards are shown with reduced visibility.

Examples:

ai -policy "teacher training": finds resources about AI and teacher training, excluding anything tagged "policy".
tag:ethics OR tag:privacy: shows content tagged with either ethics or privacy - useful for comparing values-focused resources.
title:"rubric design" content:feedback: finds resources with that exact phrase in the title and discussion of feedback in the content.
tag:"student voice" -tag:governance: filters content focused on student voice, excluding governance-related material.

💡 Combine these search terms with the category selector in the toolbar to further narrow your results (e.g. select category "Practice" and search tag:rubric).

It may look technical, but it's educationally powerful - showing how AI systems filter, include, and exclude information based on structure and metadata. These are the same principles behind real-world search and AI tools.

Educational Purpose

For teachers, trainers and school teams, the index is a low-threshold learning tool. It demonstrates how data and algorithmic choices shape what becomes visible. By using it, you learn to:

Distinguish between content and structure of information;
Recognise bias, transparency and traceability in practice;
Demonstrate to colleagues or students how search results are constructed.

The tool fits naturally into lessons on digital literacy, media awareness and AI in the classroom.

Link to AI Literacy

Table 1. Link to AI Literacy
Domain	What you practise	Guiding question
Understanding	Knowing how search and filter systems work	“What changes if I add 'Policy'?”
Critical Thinking	Seeing how design choices affect results	“Which cards vanish when I select the 'Policy' category?”
Ethical Awareness	Exploring transparency and autonomy	“Who sets the default sort order?”
Practical Use	Searching, combining and comparing effectively	“How can I find all 'rubric' items in 'Practice' category?”

These dimensions align with UNESCO and EU frameworks for AI literacy: knowledge, skills, attitude and responsibility.

Use in Teams or Classrooms

Use the Light Index as a conversation starter on responsible AI use. Each task connects hands-on exploration with one or more of the RAI principles.

Suggested activities

Human-centred: Explore three resources on the same topic in different categories. How do human labels shape what appears?
Fair & transparent: Reflect on which search gave the most diverse results - and why.
Safe & reliable: Design an extra filter for your subject area. How would you keep it clear and consistent?
Accountable & privacy-aware: Analyse what the interface remembers or ignores. What does that mean for trust?
Sustainable: Discuss why local, cookie-free design reduces environmental and data impact.

A simple interface becomes a window into algorithmic thinking and ethical design, linking everyday search choices to the values of responsible, human-centred AI in education.

Our Mission

This app reflects our broader mission:

We help schools use AI wisely - from policy to classroom practice. We don't sell AI apps; we build knowledge, routines and example projects that show how it can be done.

By experimenting with the Light Index, you'll experience that transparency, control and critical understanding aren't technical extras - they're learning goals.

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